Next generation sequencing (NGS) is of great significance for genetic improvement. Some of the most common application of NGS is the identification of the genomic variants, genes and sequence mutations. Mining of genomic variants such as single nucleotide polymorphisms (SNPs) from raw sequences involves several steps and use of numerous bioinformatics tools in a systematic manner. This paper reviews the components of a pipeline that calls SNPs from NGS data. The SNP calling pipeline includes base calling, quality checks, reads trimming, alignment of the quality reads to the reference genome, quality score recalibration, visualization and SNP identification. The final step of the pipeline is making biological sense out of the SNPs data, which involves filtering and annotation of the candidates SNPs.
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